This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.
Load the required libraries. If you don’t have them installed, please do by running install.packages()
library(plotly)## Loading required package: ggplot2##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
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## last_plot## The following object is masked from 'package:stats':
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## filter## The following object is masked from 'package:graphics':
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## layoutlibrary(stringr)
library(reshape2)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, unionlibrary(readr)Load the NMR binned csv. Just adapt the path to location of your file. You can use autocompletion using the tab key
Binning_Fusarium_sh1 <- read_csv("../../data/Binning_Fusarium_matz_center_named.csv")##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## .default = col_double()
## )
## ℹ Use `spec()` for the full column specifications.Lets have a look at the first rows of this file
head(Binning_Fusarium_sh1)OK. Be sure to have ppm on the columns and fraction numbers as rows. Now we transform the dataframe as a matrix
DTz <- as.matrix(data.frame(Binning_Fusarium_sh1))Lets have a look at the structure of the file
str(DTz)## num [1:135, 1:1603] 1 2 3 4 5 6 7 8 9 10 ...
## - attr(*, "dimnames")=List of 2
## ..$ : NULL
## ..$ : chr [1:1603] "X." "X.1.00831" "X.0.998305" "X.0.988305" ...Now we’ll remove the row indexes
DTz <- DTz[,-1] And we set the matrix row and colnames according to the ones of the df
colnames(DTz) <- colnames(Binning_Fusarium_sh1)[-1]
rownames(DTz) <- rownames(Binning_Fusarium_sh1)Let’s transform these data in the long form
mtrx.melt <- melt(DTz, id.vars = c('sample', 'ppm'), measure.vars = 'int')
names(mtrx.melt) <- c('sample', 'ppm', 'int')Now we can plot a quick 3Dplot to have an overview of the data
p <- plot_ly(z = ~DTz) %>% add_surface()
pOK so now we want to remove the annoying signals corresponding to the solvents. We can check at the colunms name and note their numbers. Example its DMSO > signals at 2.5 ppm I want to delete columns 350,351 and 352.
colnames(DTz)## [1] "-1.00831" "-0.998305" "-0.988305" "-0.978304" "-0.968304"
## [6] "-0.958303" "-0.948303" "-0.938302" "-0.928302" "-0.918301"
## [11] "-0.9083" "-0.8983" "-0.888299" "-0.878299" "-0.868298"
## [16] "-0.858298" "-0.848297" "-0.838297" "-0.828296" "-0.818296"
## [21] "-0.808295" "-0.798295" "-0.788294" "-0.778294" "-0.768293"
## [26] "-0.758292" "-0.748292" "-0.738291" "-0.728291" "-0.71829"
## [31] "-0.70829" "-0.698289" "-0.688289" "-0.678288" "-0.668288"
## [36] "-0.658287" "-0.648287" "-0.638286" "-0.628285" "-0.618285"
## [41] "-0.608284" "-0.598284" "-0.588283" "-0.578283" "-0.568282"
## [46] "-0.558282" "-0.548281" "-0.538281" "-0.52828" "-0.51828"
## [51] "-0.508279" "-0.498279" "-0.488278" "-0.478277" "-0.468277"
## [56] "-0.458276" "-0.448276" "-0.438275" "-0.428275" "-0.418274"
## [61] "-0.408274" "-0.398273" "-0.388273" "-0.378272" "-0.368272"
## [66] "-0.358271" "-0.348271" "-0.33827" "-0.328269" "-0.318269"
## [71] "-0.308268" "-0.298268" "-0.288267" "-0.278267" "-0.268266"
## [76] "-0.258266" "-0.248265" "-0.238265" "-0.228264" "-0.218264"
## [81] "-0.208263" "-0.198262" "-0.188262" "-0.178261" "-0.168261"
## [86] "-0.15826" "-0.14826" "-0.138259" "-0.128259" "-0.118258"
## [91] "-0.108258" "-0.0982571" "-0.0882566" "-0.0782561" "-0.0682555"
## [96] "-0.058255" "-0.0482545" "-0.0382539" "-0.0282534" "-0.0182529"
## [101] "-0.00825233" "0.00174821" "0.0117487" "0.0217493" "0.0317498"
## [106] "0.0417503" "0.0517509" "0.0617514" "0.071752" "0.0817525"
## [111] "0.091753" "0.101754" "0.111754" "0.121755" "0.131755"
## [116] "0.141756" "0.151756" "0.161757" "0.171757" "0.181758"
## [121] "0.191758" "0.201759" "0.211759" "0.22176" "0.231761"
## [126] "0.241761" "0.251762" "0.261762" "0.271763" "0.281763"
## [131] "0.291764" "0.301764" "0.311765" "0.321765" "0.331766"
## [136] "0.341766" "0.351767" "0.361767" "0.371768" "0.381769"
## [141] "0.391769" "0.40177" "0.41177" "0.421771" "0.431771"
## [146] "0.441772" "0.451772" "0.461773" "0.471773" "0.481774"
## [151] "0.491774" "0.501775" "0.511775" "0.521776" "0.531777"
## [156] "0.541777" "0.551778" "0.561778" "0.571779" "0.581779"
## [161] "0.59178" "0.60178" "0.611781" "0.621781" "0.631782"
## [166] "0.641782" "0.651783" "0.661784" "0.671784" "0.681785"
## [171] "0.691785" "0.701786" "0.711786" "0.721787" "0.731787"
## [176] "0.741788" "0.751788" "0.761789" "0.771789" "0.78179"
## [181] "0.79179" "0.801791" "0.811792" "0.821792" "0.831793"
## [186] "0.841793" "0.851794" "0.861794" "0.871795" "0.881795"
## [191] "0.891796" "0.901796" "0.911797" "0.921797" "0.931798"
## [196] "0.941799" "0.951799" "0.9618" "0.9718" "0.981801"
## [201] "0.991801" "1.0018" "1.0118" "1.0218" "1.0318"
## [206] "1.0418" "1.0518" "1.0618" "1.07181" "1.08181"
## [211] "1.09181" "1.10181" "1.11181" "1.12181" "1.13181"
## [216] "1.14181" "1.15181" "1.16181" "1.17181" "1.18181"
## [221] "1.19181" "1.20181" "1.21181" "1.22181" "1.23181"
## [226] "1.24181" "1.25182" "1.26182" "1.27182" "1.28182"
## [231] "1.29182" "1.30182" "1.31182" "1.32182" "1.33182"
## [236] "1.34182" "1.35182" "1.36182" "1.37182" "1.38182"
## [241] "1.39182" "1.40182" "1.41182" "1.42182" "1.43182"
## [246] "1.44183" "1.45183" "1.46183" "1.47183" "1.48183"
## [251] "1.49183" "1.50183" "1.51183" "1.52183" "1.53183"
## [256] "1.54183" "1.55183" "1.56183" "1.57183" "1.58183"
## [261] "1.59183" "1.60183" "1.61183" "1.62183" "1.63184"
## [266] "1.64184" "1.65184" "1.66184" "1.67184" "1.68184"
## [271] "1.69184" "1.70184" "1.71184" "1.72184" "1.73184"
## [276] "1.74184" "1.75184" "1.76184" "1.77184" "1.78184"
## [281] "1.79184" "1.80184" "1.81185" "1.82185" "1.83185"
## [286] "1.84185" "1.85185" "1.86185" "1.87185" "1.88185"
## [291] "1.89185" "1.90185" "1.91185" "1.92185" "1.93185"
## [296] "1.94185" "1.95185" "1.96185" "1.97185" "1.98185"
## [301] "1.99185" "2.00186" "2.01186" "2.02186" "2.03186"
## [306] "2.04186" "2.05186" "2.06186" "2.07186" "2.08186"
## [311] "2.09186" "2.10186" "2.11186" "2.12186" "2.13186"
## [316] "2.14186" "2.15186" "2.16186" "2.17186" "2.18186"
## [321] "2.19187" "2.20187" "2.21187" "2.22187" "2.23187"
## [326] "2.24187" "2.25187" "2.26187" "2.27187" "2.28187"
## [331] "2.29187" "2.30187" "2.31187" "2.32187" "2.33187"
## [336] "2.34187" "2.35187" "2.36187" "2.37188" "2.38188"
## [341] "2.39188" "2.40188" "2.41188" "2.42188" "2.43188"
## [346] "2.44188" "2.45188" "2.46188" "2.47188" "2.48188"
## [351] "2.49188" "2.50188" "2.51188" "2.52188" "2.53188"
## [356] "2.54188" "2.55188" "2.56189" "2.57189" "2.58189"
## [361] "2.59189" "2.60189" "2.61189" "2.62189" "2.63189"
## [366] "2.64189" "2.65189" "2.66189" "2.67189" "2.68189"
## [371] "2.69189" "2.70189" "2.71189" "2.72189" "2.73189"
## [376] "2.74189" "2.7519" "2.7619" "2.7719" "2.7819"
## [381] "2.7919" "2.8019" "2.8119" "2.8219" "2.8319"
## [386] "2.8419" "2.8519" "2.8619" "2.8719" "2.8819"
## [391] "2.8919" "2.9019" "2.9119" "2.9219" "2.9319"
## [396] "2.94191" "2.95191" "2.96191" "2.97191" "2.98191"
## [401] "2.99191" "3.00191" "3.01191" "3.02191" "3.03191"
## [406] "3.04191" "3.05191" "3.06191" "3.07191" "3.08191"
## [411] "3.09191" "3.10191" "3.11191" "3.12192" "3.13192"
## [416] "3.14192" "3.15192" "3.16192" "3.17192" "3.18192"
## [421] "3.19192" "3.20192" "3.21192" "3.22192" "3.23192"
## [426] "3.24192" "3.25192" "3.26192" "3.27192" "3.28192"
## [431] "3.29192" "3.30192" "3.31193" "3.32193" "3.33193"
## [436] "3.34193" "3.35193" "3.36193" "3.37193" "3.38193"
## [441] "3.39193" "3.40193" "3.41193" "3.42193" "3.43193"
## [446] "3.44193" "3.45193" "3.46193" "3.47193" "3.48193"
## [451] "3.49193" "3.50194" "3.51194" "3.52194" "3.53194"
## [456] "3.54194" "3.55194" "3.56194" "3.57194" "3.58194"
## [461] "3.59194" "3.60194" "3.61194" "3.62194" "3.63194"
## [466] "3.64194" "3.65194" "3.66194" "3.67194" "3.68195"
## [471] "3.69195" "3.70195" "3.71195" "3.72195" "3.73195"
## [476] "3.74195" "3.75195" "3.76195" "3.77195" "3.78195"
## [481] "3.79195" "3.80195" "3.81195" "3.82195" "3.83195"
## [486] "3.84195" "3.85195" "3.86195" "3.87196" "3.88196"
## [491] "3.89196" "3.90196" "3.91196" "3.92196" "3.93196"
## [496] "3.94196" "3.95196" "3.96196" "3.97196" "3.98196"
## [501] "3.99196" "4.00196" "4.01196" "4.02196" "4.03196"
## [506] "4.04196" "4.05196" "4.06197" "4.07197" "4.08197"
## [511] "4.09197" "4.10197" "4.11197" "4.12197" "4.13197"
## [516] "4.14197" "4.15197" "4.16197" "4.17197" "4.18197"
## [521] "4.19197" "4.20197" "4.21197" "4.22197" "4.23197"
## [526] "4.24198" "4.25198" "4.26198" "4.27198" "4.28198"
## [531] "4.29198" "4.30198" "4.31198" "4.32198" "4.33198"
## [536] "4.34198" "4.35198" "4.36198" "4.37198" "4.38198"
## [541] "4.39198" "4.40198" "4.41198" "4.42198" "4.43199"
## [546] "4.44199" "4.45199" "4.46199" "4.47199" "4.48199"
## [551] "4.49199" "4.50199" "4.51199" "4.52199" "4.53199"
## [556] "4.54199" "4.55199" "4.56199" "4.57199" "4.58199"
## [561] "4.59199" "4.60199" "4.61199" "4.622" "4.632"
## [566] "4.642" "4.652" "4.662" "4.672" "4.682"
## [571] "4.692" "4.702" "4.712" "4.722" "4.732"
## [576] "4.742" "4.752" "4.762" "4.772" "4.782"
## [581] "4.792" "4.80201" "4.81201" "4.82201" "4.83201"
## [586] "4.84201" "4.85201" "4.86201" "4.87201" "4.88201"
## [591] "4.89201" "4.90201" "4.91201" "4.92201" "4.93201"
## [596] "4.94201" "4.95201" "4.96201" "4.97201" "4.98201"
## [601] "4.99202" "5.00202" "5.01202" "5.02202" "5.03202"
## [606] "5.04202" "5.05202" "5.06202" "5.07202" "5.08202"
## [611] "5.09202" "5.10202" "5.11202" "5.12202" "5.13202"
## [616] "5.14202" "5.15202" "5.16202" "5.17202" "5.18203"
## [621] "5.19203" "5.20203" "5.21203" "5.22203" "5.23203"
## [626] "5.24203" "5.25203" "5.26203" "5.27203" "5.28203"
## [631] "5.29203" "5.30203" "5.31203" "5.32203" "5.33203"
## [636] "5.34203" "5.35203" "5.36203" "5.37204" "5.38204"
## [641] "5.39204" "5.40204" "5.41204" "5.42204" "5.43204"
## [646] "5.44204" "5.45204" "5.46204" "5.47204" "5.48204"
## [651] "5.49204" "5.50204" "5.51204" "5.52204" "5.53204"
## [656] "5.54204" "5.55205" "5.56205" "5.57205" "5.58205"
## [661] "5.59205" "5.60205" "5.61205" "5.62205" "5.63205"
## [666] "5.64205" "5.65205" "5.66205" "5.67205" "5.68205"
## [671] "5.69205" "5.70205" "5.71205" "5.72205" "5.73205"
## [676] "5.74206" "5.75206" "5.76206" "5.77206" "5.78206"
## [681] "5.79206" "5.80206" "5.81206" "5.82206" "5.83206"
## [686] "5.84206" "5.85206" "5.86206" "5.87206" "5.88206"
## [691] "5.89206" "5.90206" "5.91206" "5.92206" "5.93207"
## [696] "5.94207" "5.95207" "5.96207" "5.97207" "5.98207"
## [701] "5.99207" "6.00207" "6.01207" "6.02207" "6.03207"
## [706] "6.04207" "6.05207" "6.06207" "6.07207" "6.08207"
## [711] "6.09207" "6.10207" "6.11208" "6.12208" "6.13208"
## [716] "6.14208" "6.15208" "6.16208" "6.17208" "6.18208"
## [721] "6.19208" "6.20208" "6.21208" "6.22208" "6.23208"
## [726] "6.24208" "6.25208" "6.26208" "6.27208" "6.28208"
## [731] "6.29208" "6.30209" "6.31209" "6.32209" "6.33209"
## [736] "6.34209" "6.35209" "6.36209" "6.37209" "6.38209"
## [741] "6.39209" "6.40209" "6.41209" "6.42209" "6.43209"
## [746] "6.44209" "6.45209" "6.46209" "6.47209" "6.48209"
## [751] "6.4921" "6.5021" "6.5121" "6.5221" "6.5321"
## [756] "6.5421" "6.5521" "6.5621" "6.5721" "6.5821"
## [761] "6.5921" "6.6021" "6.6121" "6.6221" "6.6321"
## [766] "6.6421" "6.6521" "6.6621" "6.67211" "6.68211"
## [771] "6.69211" "6.70211" "6.71211" "6.72211" "6.73211"
## [776] "6.74211" "6.75211" "6.76211" "6.77211" "6.78211"
## [781] "6.79211" "6.80211" "6.81211" "6.82211" "6.83211"
## [786] "6.84211" "6.85211" "6.86212" "6.87212" "6.88212"
## [791] "6.89212" "6.90212" "6.91212" "6.92212" "6.93212"
## [796] "6.94212" "6.95212" "6.96212" "6.97212" "6.98212"
## [801] "6.99212" "7.00212" "7.01212" "7.02212" "7.03212"
## [806] "7.04212" "7.05213" "7.06213" "7.07213" "7.08213"
## [811] "7.09213" "7.10213" "7.11213" "7.12213" "7.13213"
## [816] "7.14213" "7.15213" "7.16213" "7.17213" "7.18213"
## [821] "7.19213" "7.20213" "7.21213" "7.22213" "7.23214"
## [826] "7.24214" "7.25214" "7.26214" "7.27214" "7.28214"
## [831] "7.29214" "7.30214" "7.31214" "7.32214" "7.33214"
## [836] "7.34214" "7.35214" "7.36214" "7.37214" "7.38214"
## [841] "7.39214" "7.40214" "7.41214" "7.42215" "7.43215"
## [846] "7.44215" "7.45215" "7.46215" "7.47215" "7.48215"
## [851] "7.49215" "7.50215" "7.51215" "7.52215" "7.53215"
## [856] "7.54215" "7.55215" "7.56215" "7.57215" "7.58215"
## [861] "7.59215" "7.60215" "7.61216" "7.62216" "7.63216"
## [866] "7.64216" "7.65216" "7.66216" "7.67216" "7.68216"
## [871] "7.69216" "7.70216" "7.71216" "7.72216" "7.73216"
## [876] "7.74216" "7.75216" "7.76216" "7.77216" "7.78216"
## [881] "7.79216" "7.80217" "7.81217" "7.82217" "7.83217"
## [886] "7.84217" "7.85217" "7.86217" "7.87217" "7.88217"
## [891] "7.89217" "7.90217" "7.91217" "7.92217" "7.93217"
## [896] "7.94217" "7.95217" "7.96217" "7.97217" "7.98218"
## [901] "7.99218" "8.00218" "8.01218" "8.02218" "8.03218"
## [906] "8.04218" "8.05218" "8.06218" "8.07218" "8.08218"
## [911] "8.09218" "8.10218" "8.11218" "8.12218" "8.13218"
## [916] "8.14218" "8.15218" "8.16218" "8.17219" "8.18219"
## [921] "8.19219" "8.20219" "8.21219" "8.22219" "8.23219"
## [926] "8.24219" "8.25219" "8.26219" "8.27219" "8.28219"
## [931] "8.29219" "8.30219" "8.31219" "8.32219" "8.33219"
## [936] "8.34219" "8.35219" "8.3622" "8.3722" "8.3822"
## [941] "8.3922" "8.4022" "8.4122" "8.4222" "8.4322"
## [946] "8.4422" "8.4522" "8.4622" "8.4722" "8.4822"
## [951] "8.4922" "8.5022" "8.5122" "8.5222" "8.5322"
## [956] "8.54221" "8.55221" "8.56221" "8.57221" "8.58221"
## [961] "8.59221" "8.60221" "8.61221" "8.62221" "8.63221"
## [966] "8.64221" "8.65221" "8.66221" "8.67221" "8.68221"
## [971] "8.69221" "8.70221" "8.71221" "8.72221" "8.73222"
## [976] "8.74222" "8.75222" "8.76222" "8.77222" "8.78222"
## [981] "8.79222" "8.80222" "8.81222" "8.82222" "8.83222"
## [986] "8.84222" "8.85222" "8.86222" "8.87222" "8.88222"
## [991] "8.89222" "8.90222" "8.91222" "8.92223" "8.93223"
## [996] "8.94223" "8.95223" "8.96223" "8.97223" "8.98223"
## [1001] "8.99223" "9.00223" "9.01223" "9.02223" "9.03223"
## [1006] "9.04223" "9.05223" "9.06223" "9.07223" "9.08223"
## [1011] "9.09223" "9.10224" "9.11224" "9.12224" "9.13224"
## [1016] "9.14224" "9.15224" "9.16224" "9.17224" "9.18224"
## [1021] "9.19224" "9.20224" "9.21224" "9.22224" "9.23224"
## [1026] "9.24224" "9.25224" "9.26224" "9.27224" "9.28224"
## [1031] "9.29225" "9.30225" "9.31225" "9.32225" "9.33225"
## [1036] "9.34225" "9.35225" "9.36225" "9.37225" "9.38225"
## [1041] "9.39225" "9.40225" "9.41225" "9.42225" "9.43225"
## [1046] "9.44225" "9.45225" "9.46225" "9.47225" "9.48226"
## [1051] "9.49226" "9.50226" "9.51226" "9.52226" "9.53226"
## [1056] "9.54226" "9.55226" "9.56226" "9.57226" "9.58226"
## [1061] "9.59226" "9.60226" "9.61226" "9.62226" "9.63226"
## [1066] "9.64226" "9.65226" "9.66227" "9.67227" "9.68227"
## [1071] "9.69227" "9.70227" "9.71227" "9.72227" "9.73227"
## [1076] "9.74227" "9.75227" "9.76227" "9.77227" "9.78227"
## [1081] "9.79227" "9.80227" "9.81227" "9.82227" "9.83227"
## [1086] "9.84227" "9.85228" "9.86228" "9.87228" "9.88228"
## [1091] "9.89228" "9.90228" "9.91228" "9.92228" "9.93228"
## [1096] "9.94228" "9.95228" "9.96228" "9.97228" "9.98228"
## [1101] "9.99228" "10.0023" "10.0123" "10.0223" "10.0323"
## [1106] "10.0423" "10.0523" "10.0623" "10.0723" "10.0823"
## [1111] "10.0923" "10.1023" "10.1123" "10.1223" "10.1323"
## [1116] "10.1423" "10.1523" "10.1623" "10.1723" "10.1823"
## [1121] "10.1923" "10.2023" "10.2123" "10.2223" "10.2323"
## [1126] "10.2423" "10.2523" "10.2623" "10.2723" "10.2823"
## [1131] "10.2923" "10.3023" "10.3123" "10.3223" "10.3323"
## [1136] "10.3423" "10.3523" "10.3623" "10.3723" "10.3823"
## [1141] "10.3923" "10.4023" "10.4123" "10.4223" "10.4323"
## [1146] "10.4423" "10.4523" "10.4623" "10.4723" "10.4823"
## [1151] "10.4923" "10.5023" "10.5123" "10.5223" "10.5323"
## [1156] "10.5423" "10.5523" "10.5623" "10.5723" "10.5823"
## [1161] "10.5923" "10.6023" "10.6123" "10.6223" "10.6323"
## [1166] "10.6423" "10.6523" "10.6623" "10.6723" "10.6823"
## [1171] "10.6923" "10.7023" "10.7123" "10.7223" "10.7323"
## [1176] "10.7423" "10.7523" "10.7623" "10.7723" "10.7823"
## [1181] "10.7923" "10.8023" "10.8123" "10.8223" "10.8323"
## [1186] "10.8423" "10.8523" "10.8623" "10.8723" "10.8823"
## [1191] "10.8923" "10.9023" "10.9123" "10.9223" "10.9323"
## [1196] "10.9423" "10.9523" "10.9623" "10.9723" "10.9823"
## [1201] "10.9923" "11.0023" "11.0123" "11.0223" "11.0323"
## [1206] "11.0423" "11.0523" "11.0623" "11.0723" "11.0823"
## [1211] "11.0923" "11.1023" "11.1123" "11.1223" "11.1323"
## [1216] "11.1423" "11.1523" "11.1623" "11.1723" "11.1823"
## [1221] "11.1923" "11.2023" "11.2123" "11.2223" "11.2323"
## [1226] "11.2423" "11.2524" "11.2624" "11.2724" "11.2824"
## [1231] "11.2924" "11.3024" "11.3124" "11.3224" "11.3324"
## [1236] "11.3424" "11.3524" "11.3624" "11.3724" "11.3824"
## [1241] "11.3924" "11.4024" "11.4124" "11.4224" "11.4324"
## [1246] "11.4424" "11.4524" "11.4624" "11.4724" "11.4824"
## [1251] "11.4924" "11.5024" "11.5124" "11.5224" "11.5324"
## [1256] "11.5424" "11.5524" "11.5624" "11.5724" "11.5824"
## [1261] "11.5924" "11.6024" "11.6124" "11.6224" "11.6324"
## [1266] "11.6424" "11.6524" "11.6624" "11.6724" "11.6824"
## [1271] "11.6924" "11.7024" "11.7124" "11.7224" "11.7324"
## [1276] "11.7424" "11.7524" "11.7624" "11.7724" "11.7824"
## [1281] "11.7924" "11.8024" "11.8124" "11.8224" "11.8324"
## [1286] "11.8424" "11.8524" "11.8624" "11.8724" "11.8824"
## [1291] "11.8924" "11.9024" "11.9124" "11.9224" "11.9324"
## [1296] "11.9424" "11.9524" "11.9624" "11.9724" "11.9824"
## [1301] "11.9924" "12.0024" "12.0124" "12.0224" "12.0324"
## [1306] "12.0424" "12.0524" "12.0624" "12.0724" "12.0824"
## [1311] "12.0924" "12.1024" "12.1124" "12.1224" "12.1324"
## [1316] "12.1424" "12.1524" "12.1624" "12.1724" "12.1824"
## [1321] "12.1924" "12.2024" "12.2124" "12.2224" "12.2324"
## [1326] "12.2424" "12.2524" "12.2624" "12.2724" "12.2824"
## [1331] "12.2924" "12.3024" "12.3124" "12.3224" "12.3324"
## [1336] "12.3424" "12.3524" "12.3624" "12.3724" "12.3824"
## [1341] "12.3924" "12.4024" "12.4124" "12.4224" "12.4324"
## [1346] "12.4424" "12.4524" "12.4624" "12.4724" "12.4824"
## [1351] "12.4924" "12.5024" "12.5124" "12.5224" "12.5324"
## [1356] "12.5424" "12.5524" "12.5624" "12.5724" "12.5824"
## [1361] "12.5924" "12.6024" "12.6124" "12.6224" "12.6324"
## [1366] "12.6424" "12.6524" "12.6624" "12.6724" "12.6824"
## [1371] "12.6924" "12.7024" "12.7124" "12.7224" "12.7324"
## [1376] "12.7424" "12.7524" "12.7624" "12.7724" "12.7824"
## [1381] "12.7924" "12.8024" "12.8124" "12.8224" "12.8324"
## [1386] "12.8424" "12.8524" "12.8624" "12.8724" "12.8824"
## [1391] "12.8924" "12.9024" "12.9124" "12.9224" "12.9324"
## [1396] "12.9424" "12.9524" "12.9624" "12.9724" "12.9824"
## [1401] "12.9924" "13.0024" "13.0124" "13.0224" "13.0324"
## [1406] "13.0424" "13.0524" "13.0624" "13.0724" "13.0824"
## [1411] "13.0924" "13.1024" "13.1124" "13.1225" "13.1325"
## [1416] "13.1425" "13.1525" "13.1625" "13.1725" "13.1825"
## [1421] "13.1925" "13.2025" "13.2125" "13.2225" "13.2325"
## [1426] "13.2425" "13.2525" "13.2625" "13.2725" "13.2825"
## [1431] "13.2925" "13.3025" "13.3125" "13.3225" "13.3325"
## [1436] "13.3425" "13.3525" "13.3625" "13.3725" "13.3825"
## [1441] "13.3925" "13.4025" "13.4125" "13.4225" "13.4325"
## [1446] "13.4425" "13.4525" "13.4625" "13.4725" "13.4825"
## [1451] "13.4925" "13.5025" "13.5125" "13.5225" "13.5325"
## [1456] "13.5425" "13.5525" "13.5625" "13.5725" "13.5825"
## [1461] "13.5925" "13.6025" "13.6125" "13.6225" "13.6325"
## [1466] "13.6425" "13.6525" "13.6625" "13.6725" "13.6825"
## [1471] "13.6925" "13.7025" "13.7125" "13.7225" "13.7325"
## [1476] "13.7425" "13.7525" "13.7625" "13.7725" "13.7825"
## [1481] "13.7925" "13.8025" "13.8125" "13.8225" "13.8325"
## [1486] "13.8425" "13.8525" "13.8625" "13.8725" "13.8825"
## [1491] "13.8925" "13.9025" "13.9125" "13.9225" "13.9325"
## [1496] "13.9425" "13.9525" "13.9625" "13.9725" "13.9825"
## [1501] "13.9925" "14.0025" "14.0125" "14.0225" "14.0325"
## [1506] "14.0425" "14.0525" "14.0625" "14.0725" "14.0825"
## [1511] "14.0925" "14.1025" "14.1125" "14.1225" "14.1325"
## [1516] "14.1425" "14.1525" "14.1625" "14.1725" "14.1825"
## [1521] "14.1925" "14.2025" "14.2125" "14.2225" "14.2325"
## [1526] "14.2425" "14.2525" "14.2625" "14.2725" "14.2825"
## [1531] "14.2925" "14.3025" "14.3125" "14.3225" "14.3325"
## [1536] "14.3425" "14.3525" "14.3625" "14.3725" "14.3825"
## [1541] "14.3925" "14.4025" "14.4125" "14.4225" "14.4325"
## [1546] "14.4425" "14.4525" "14.4625" "14.4725" "14.4825"
## [1551] "14.4925" "14.5025" "14.5125" "14.5225" "14.5325"
## [1556] "14.5425" "14.5525" "14.5625" "14.5725" "14.5825"
## [1561] "14.5925" "14.6025" "14.6125" "14.6225" "14.6325"
## [1566] "14.6425" "14.6525" "14.6625" "14.6725" "14.6825"
## [1571] "14.6925" "14.7025" "14.7125" "14.7225" "14.7325"
## [1576] "14.7425" "14.7525" "14.7625" "14.7725" "14.7825"
## [1581] "14.7925" "14.8025" "14.8125" "14.8225" "14.8325"
## [1586] "14.8425" "14.8525" "14.8625" "14.8725" "14.8825"
## [1591] "14.8925" "14.9025" "14.9125" "14.9225" "14.9325"
## [1596] "14.9425" "14.9525" "14.9625" "14.9725" "14.9825"
## [1601] "14.9926" "15.0026"DTzred <- DTz[,-348:-352]Now lets plot again …. Does it looks better ?
p <- plot_ly(z = ~DTzred) %>% add_surface()
pElse repeat the previous step For this execute the following code. Be sure to run it on the previously cleaned object. In this case DTzred Be sure to check again the columns numbers sinsce these have changed
colnames(DTzred)
DTzred <- DTzred[,-348:-352]Now that you have the cleaned data object lets have a look at the 2d map. Be patient, this one is longer to plot.
p <- plot_ly(mtrx.melt, x = ~sample, y = ~ppm, z = ~int, type = "contour",
colors = 'YlOrRd',
autocontour = F,
contours = list(
start = 10000,
end = 1200000,
size = 5000
)
)
pIf you want to plot the map with ppm on the x-axis just reverse the axis order. Play with start value (to fix the noise) and size value to fix the contour space. Change color if you wish by changing the color field. For more info on 2d contour plot with plotly check https://plot.ly/r/contour-plots/
p <- plot_ly(mtrx.melt, x = ~ppm, y = ~sample, z = ~int, type = "contour",
autocontour = F,
colors = 'YlOrRd',
contours = list(
start = 10000,
end = 1200000,
size = 50000
)
) %>% layout(xaxis = list(autorange = "reversed"))
pWhen you save the notebook, an HTML file containing the code and output will be saved alongside it (click the Preview button or press Cmd+Shift+K to preview the HTML file).
The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike Knit, Preview does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed.